Audio Classification
Transformers
Safetensors
audio-spectrogram-transformer
Generated from Trainer
Eval Results (legacy)
Instructions to use Vladimirlv/ast-finetuned-audioset-10-10-0.4593-heart-sounds with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vladimirlv/ast-finetuned-audioset-10-10-0.4593-heart-sounds with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Vladimirlv/ast-finetuned-audioset-10-10-0.4593-heart-sounds")# Load model directly from transformers import AutoFeatureExtractor, AutoModelForAudioClassification extractor = AutoFeatureExtractor.from_pretrained("Vladimirlv/ast-finetuned-audioset-10-10-0.4593-heart-sounds") model = AutoModelForAudioClassification.from_pretrained("Vladimirlv/ast-finetuned-audioset-10-10-0.4593-heart-sounds") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a5bdcd7c54cbc85a0aea5b3a868ae7bacafe636e3d1190bb03d39dec9704ac0d
- Size of remote file:
- 345 MB
- SHA256:
- a6ce20c1e95671a0fd0b59cb5fae2d3188100cb9c81844b709c1af08c9bf4983
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.